(a) Field of the Invention
The present invention relates to a biometric figure identification system using a figure's face image.
The present invention further relates to a technique for adaptively recognizing a figure by considering a face attribute of a watch list in a condition in which lighting is non-uniform and a face rotation angle range of the image is wide.
(b) Description of the Related Art
Techniques for recognizing a figure according to a face image have been a matter of concern and interest for several decades. A human face image identification system is based on a method of comparing a similar model that is acquired according to an input analysis image and a known face model (or image) of a specific person. Most of the above-noted systems are required to compare a frontal face image that has been acquired under a condition of controlled lighting and an image only some years ago. The requirement condition has restricted the fields to which the actual recognition system is applied.
U.S. Pat. No. 7,142,697[1] of “Face Recognition System and Process Invariable by Pose” proposes a face recognition method based on a method for manufacturing a classifier according to camera angles to a face. Identification results are output by combining results of the classifiers. A face image to be recognized is coded by using the PCA scheme. A neural network is used as a basic classifier, its input includes PCA vectors, and its output includes measured approximate values that are coded with registered classes. The neural network is used again so as to output results, an input unit of the neural network receives similarity measurement values from first-stage classifiers, and an output unit thereof proposes a shape displayed on the figure picture and checks the recognized class. Accordingly, the above-noted invention can recognize a face when the face rotation angle has a wide range. However, it is difficult to use the neural network cascade in real-time because it uses a large amount of computation.
U.S. Pat. No. 7,203,346[2] of “Method and Device for Recognizing a Face by using a Component Based Face Describer” proposes a face recognition algorithm for measuring similarity according to individual patches (e.g., eyes, lips, nose, and forehead) of a face image, and comparing two face images. Calculated weights are added to the calculated measurement values, and the similarity of the two images is finally measured. Further, temporary calculation estimation on the figure appearance is performed by the LDA method, and acquired information is used to compare the two faces. An image coding process on the face parts is performed by the LDA method. The above-noted method is efficient for a case in which lighting conditions are not complex and the face view is not the front of the face. However, the algorithm does not consider relative type and image characteristics of the registered user's face.
U.S. Pat. No. 7,031,499[3] of “Target Recognition System” recognizes the face based on a filter set and a simple classifier amplification method, generates a classifier cascade, and in this instance, adaptively sets values of the cascade elements. The filter is directly selected by specific registered users.
U.S. Pat. No. 6,826,300[4] of “Classification Based on Features” proposes a method for measuring image similarity using a template. In this instance, the invention uses the augmented Gabor feature vector of the face image based on the Gabor wavelet basis. The invention uses a method for selecting an important effective shape of the face image based on the PCA and LDA methods, and measures the similarity according to one of the Mahalanobis measurement method and the cosine measurement method. However, the similarity measurement and calculation method do not consider data characteristics and are not adaptive to the image of a specific watch list.
The basic drawbacks of the existing intelligent video monitoring system and the biometric system are: low precision; low operational stability in non-uniform lighting conditions; and impossibility of control on a human operation capture device.
The above information disclosed in this Background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art.